library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(randomForest)
## randomForest 4.7-1.1
## Type rfNews() to see new features/changes/bug fixes.
##
## Attaching package: 'randomForest'
##
## The following object is masked from 'package:dplyr':
##
## combine
##
## The following object is masked from 'package:ggplot2':
##
## margin
library(rfUtilities)
library(rfPermute)
## Welcome to rfPermute v2.5.2
## See rfPermuteTutorial() for a guide to the package.
library(ggpp)
## Registered S3 methods overwritten by 'ggpp':
## method from
## heightDetails.titleGrob ggplot2
## widthDetails.titleGrob ggplot2
##
## Attaching package: 'ggpp'
##
## The following object is masked from 'package:ggplot2':
##
## annotate
library(dplyr)
#########
RF<-read.csv("/Users/jamesm./Desktop/THT_Data_5082.csv")
RF<-na.omit(RF)
RF=RF[,c(21,4:13)]
set.seed(123)
richness_rf <- randomForest(RF$Physical.Activity.from.Transportation..Score ~ ., data= RF,importance=TRUE,proximity=TRUE)
richness_rf
##
## Call:
## randomForest(formula = RF$Physical.Activity.from.Transportation..Score ~ ., data = RF, importance = TRUE, proximity = TRUE)
## Type of random forest: regression
## Number of trees: 500
## No. of variables tried at each split: 3
##
## Mean of squared residuals: 329.1773
## % Var explained: 59.36
richness_perm <- rf.significance(richness_rf, RF, nperm=99, ntree=501)
richness_perm
## Number of permutations: 99
## p-value: 0.01
## Model signifiant at p = 0.01
## Model R-square: 0.5858346
## Random R-square: -0.1834711
## Random R-square variance: 0.01407312
set.seed(123)
richness_rfP<- rfPermute(RF$Physical.Activity.from.Transportation..Score ~ ., data = RF, ntree = 500,
na.action = na.omit, nrep = 99,num.cores = 3)
##
richness_dat <- importance(richness_rfP, sort.by = NULL, decreasing = TRUE)
#
richness_dat=as.data.frame(richness_dat)
##########
richness_dat$group2 <- row.names(richness_dat)
unique(richness_dat$group2)
## [1] "Commute.Mode.Share...Auto..Score"
## [2] "Commute.Mode.Share...Auto..Raw.Value"
## [3] "Commute.Mode.Share...Transit..Raw.Value"
## [4] "Commute.Mode.Share...Transit..Score"
## [5] "Commute.Mode.Share...Bicycle..Score"
## [6] "Commute.Mode.Share...Bicycle..Raw.Value"
## [7] "Commute.Mode.Share...Walk..Score"
## [8] "Commute.Mode.Share...Walk..Raw.Value"
## [9] "Complete.Streets.Policies..Raw.Value"
## [10] "Complete.Streets.Policies..Score"
#######################
richness_dat %>%
as_tibble(rownames = "names") %>%
data.frame() %>%
mutate(label = if_else(X.IncMSE.pval < 0.001,"***",
if_else(X.IncMSE.pval <0.01,"**",
if_else(X.IncMSE.pval<0.05,"*"," "))),
X.IncMSE = as.numeric(X.IncMSE)) %>%
mutate(group = if_else(label=="ns","In_sig","Sig"),
names = forcats::fct_inorder(names)) %>%
dplyr::arrange(X.IncMSE) %>%
ggplot(aes(x = group2, y = X.IncMSE))+
geom_bar(fill="tan2",stat = "identity",width=0.6,color="black")+
geom_text(aes(y = X.IncMSE + 1,label = label),size=4)+
labs(x = "", y = "%IncMSE", title="")+
theme_classic()+
#theme_bw()+
coord_flip()+
####
theme(
panel.grid = element_blank(),
panel.background =element_blank(),
#legend.position = "none",
legend.title = element_blank(),
legend.text = element_text(color="black",
size = 10,
family = "serif",
face = "bold"),
axis.title.y = element_text(size = 12,
family = "serif",
color = "black",
face = "bold"),
axis.title.x = element_text(size = 12,
family = "serif",
color = "black",
face = "bold"),
axis.text.x = element_text(size = 10,
family = "serif",
color = "black",
face = "bold"),
axis.text.y = element_text(size = 10,
family = "serif",
color = "black",
face = "bold"))
RF<-read.csv("/Users/jamesm./Desktop/THT_Data_5082.csv")
RF<-na.omit(RF)
RF=RF[,c(21,16:19)]
set.seed(123)
richness_rf <- randomForest(RF$Physical.Activity.from.Transportation..Score ~ ., data= RF,importance=TRUE,proximity=TRUE)
richness_rf
##
## Call:
## randomForest(formula = RF$Physical.Activity.from.Transportation..Score ~ ., data = RF, importance = TRUE, proximity = TRUE)
## Type of random forest: regression
## Number of trees: 500
## No. of variables tried at each split: 1
##
## Mean of squared residuals: 194.4281
## % Var explained: 76
richness_perm <- rf.significance(richness_rf, RF, nperm=99, ntree=501)
richness_perm
## Number of permutations: 99
## p-value: 0.01
## Model signifiant at p = 0.01
## Model R-square: 0.7619681
## Random R-square: -0.2068194
## Random R-square variance: 0.02194609
set.seed(123)
richness_rfP<- rfPermute(RF$Physical.Activity.from.Transportation..Score ~ ., data = RF, ntree = 500,
na.action = na.omit, nrep = 99,num.cores = 3)
##
richness_dat <- importance(richness_rfP, sort.by = NULL, decreasing = TRUE)
#
richness_dat=as.data.frame(richness_dat)
##########
richness_dat$group2 <- row.names(richness_dat)
unique(richness_dat$group2)
## [1] "Person.Miles.of.Travel.by.Walking..Raw.Value"
## [2] "Person.Miles.of.Travel.by.Walking..Score"
## [3] "Person.Miles.of.Travel.by.Private.Vehicle..Raw.Value"
## [4] "Person.Miles.of.Travel.by.Private.Vehicle..Score"
#######################
richness_dat %>%
as_tibble(rownames = "names") %>%
data.frame() %>%
mutate(label = if_else(X.IncMSE.pval < 0.001,"***",
if_else(X.IncMSE.pval <0.01,"**",
if_else(X.IncMSE.pval<0.05,"*"," "))),
X.IncMSE = as.numeric(X.IncMSE)) %>%
mutate(group = if_else(label=="ns","In_sig","Sig"),
names = forcats::fct_inorder(names)) %>%
dplyr::arrange(X.IncMSE) %>%
ggplot(aes(x = group2, y = X.IncMSE))+
geom_bar(fill="tan2",stat = "identity",width=0.6,color="black")+
geom_text(aes(y = X.IncMSE + 1,label = label),size=4)+
labs(x = "", y = "%IncMSE", title="")+
theme_classic()+
#theme_bw()+
coord_flip()+
####
theme(
panel.grid = element_blank(),
panel.background =element_blank(),
#legend.position = "none",
legend.title = element_blank(),
legend.text = element_text(color="black",
size = 10,
family = "serif",
face = "bold"),
axis.title.y = element_text(size = 12,
family = "serif",
color = "black",
face = "bold"),
axis.title.x = element_text(size = 12,
family = "serif",
color = "black",
face = "bold"),
axis.text.x = element_text(size = 10,
family = "serif",
color = "black",
face = "bold"),
axis.text.y = element_text(size = 10,
family = "serif",
color = "black",
face = "bold"))
###################
us_states <- map_data("state")
election<-read.csv("/Users/jamesm./Desktop/THT_Data_5082.csv")
us_states_elec <- left_join(us_states, election,by="region")
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
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## filter
## The following object is masked from 'package:graphics':
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## layout
#
p0 <- ggplot(data = us_states_elec,
mapping = aes(x = long, y = lat,
group = group, fill = us_states_elec$Physical.Activity.from.Transportation..Score))+
geom_polygon(color = "gray90", size = 0.1) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
theme(legend.title = element_blank())+
scale_fill_gradientn(colours = RColorBrewer::brewer.pal(11, "RdBu"))+
labs(title = "Physical Activity from Transportation Score",fill="")+
theme_bw()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
ggplotly(p0)
## Warning: Use of `us_states_elec$Physical.Activity.from.Transportation..Score` is
## discouraged.
## ℹ Use `Physical.Activity.from.Transportation..Score` instead.
###
p0 <- ggplot(data = us_states_elec,
mapping = aes(x = long, y = lat,
group = group, fill = Commute.Mode.Share...Auto..Raw.Value))+
geom_polygon(color = "gray90", size = 0.1) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
theme(legend.title = element_blank())+
scale_fill_gradientn(colours = RColorBrewer::brewer.pal(11, "RdBu"))+
labs(title = "Commute Mode.Share Auto Raw Value",fill="")+
theme_bw()
ggplotly(p0)
####
p0 <- ggplot(data = us_states_elec,
mapping = aes(x = long, y = lat,
group = group, fill = Commute.Mode.Share...Auto..Score))+
geom_polygon(color = "gray90", size = 0.1) +
coord_map(projection = "albers", lat0 = 39, lat1 = 45) +
theme(legend.title = element_blank())+
scale_fill_gradientn(colours = RColorBrewer::brewer.pal(11, "RdBu"))+
labs(title = "Commute Mode Share Auto Score",fill="")+
theme_bw()
ggplotly(p0)